Rice Yield Estimation Using Landsat ETM+ Data and Field Observation

Abstract

Forecasting rice yield before harvest time is important to supporting planners and decision makers to predict the amount of rice that should be imported or exported and to enable governments to put in place strategic contingency plans for the redistribution of food during times of famine. This study used the Normalized Difference Vegetation Index (NDVI) of Landsat Enhanced Thematic Mapper plus (ETM+) images of rice plants to estimate rice yield based on field observation. The result showed that the rice yield could be estimated using the exponential equation of y = 0.3419e4.1587x, where y and x are rice yield and NDVI, respectively. The R2 and SE of the estimation were 0.852 and 0.077 ton/ha, respectively. An accuracy assessment of rice yield estimation using Landsat images was performed by comparing the rice yields from the estimation result and the reference data. The results show that the linear relationship with the R2 and SE of the estimation were 0.9262 and 0.21 ton/ha, respectively. The R2 is greater than or equal to 0.8, which demonstrates a strong agreement between the remotely sensed estimation and the reference data. Thus, the Landsat ETM+ has good potential for application to rice yield estimation. [ABSTRACT FROM AUTHOR] Copyright of Journal of Agricultural Science (1916-9752) is the property of Canadian Center of Science & Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)